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Animals : an open access journal from MDPI2019; 9(5); 225; doi: 10.3390/ani9050225

Text Mining Analysis to Evaluate Stakeholders’ Perception Regarding Welfare of Equines, Small Ruminants, and Turkeys.

Abstract: Welfare of animals significantly depends on how stakeholders perceive their needs and behave in a way to favor production systems that promote better welfare outcomes. This study aimed at investigating stakeholders' perception of the welfare of equines, small ruminants, and turkeys using text mining analysis. A survey composed by open-ended questions referring to different aspects of animal welfare was carried out. Text mining analysis was performed. A total of 270 surveys were filled out (horses = 122, sheep = 81, goats = 36, turkeys = 18, donkeys = 13). The respondents (41% veterinarians) came from 32 different countries. To describe welfare requirements, the words "feeding" and "water" were the most frequently used in all the species, meaning that respondents considered the welfare principle "good feeding" as the most relevant. The word "environment" was considered particularly important for turkeys, as well as the word "dry", never mentioned for other species. Horses stakeholders also considered "exercise" and "proper training" important. Goat stakeholders' concerns are often expressed by the word "space", probably because goats are often intensively managed in industrialized countries. Although the sample was too small to be representative, text mining analysis seems to be a promising method to investigate stakeholders' perception of animal welfare, as it emphasizes their real perception, without the constraints deriving by close-ended questions.
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Publication Date: 2019-05-08 PubMed ID: 31071978PubMed Central: PMC6562437DOI: 10.3390/ani9050225Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The study focuses on understanding how different stakeholders perceive the welfare of horses, small ruminants, and turkeys using text mining analysis of survey responses. According to the study, the stakeholders predominantly value feeding and water aspects, indicating their priority on good feeding practices for these animals.

Methodology

  • The researchers used text mining analysis to gauge the perceptions of various stakeholders about animal welfare. This was performed by conducting a survey with open-ended questions targeting different elements of animal welfare.
  • In total, 270 surveys were completed with responses from stakeholders involved with horses, sheep, goats, turkeys, and donkeys.
  • Respondents were from diverse backgrounds, with 41% being veterinarians, and came from 32 different countries, ensuring a wide range of perception and understanding about animal welfare.

Key Findings

  • The terms “feeding” and “water” were often used across all species, implying that stakeholders view good feeding practices as a vital aspect of animal welfare.
  • The word “environment” was also frequently used, particularly in relation to turkeys, indicating its prominence in their welfare. The term “dry” was uniquely significant for turkeys and was not mentioned for any other species.
  • For horse stakeholders, phrases like “exercise” and “proper training” were noted as important elements for animal welfare.
  • “Space” was often expressed by goat stakeholders, which possibly reflects the intensive management these animals experience in industrialized countries.

Conclusion

  • While the sample size was small and hence might not be broad enough for general conclusions, the initial findings show promise in using text mining analysis as a tool to understand stakeholders’ perception of animal welfare.
  • This method allows for authentic insights to be gathered without the limitations imposed by closed-ended questions, highlighting stakeholders’ real perception.

Cite This Article

APA
Dalla Costa E, Tranquillo V, Dai F, Minero M, Battini M, Mattiello S, Barbieri S, Ferrante V, Ferrari L, Zanella A, Canali E. (2019). Text Mining Analysis to Evaluate Stakeholders’ Perception Regarding Welfare of Equines, Small Ruminants, and Turkeys. Animals (Basel), 9(5), 225. https://doi.org/10.3390/ani9050225

Publication

Animals : an open access journal from MDPI
ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 9
Issue: 5
PII: 225

Researcher Affiliations

Dalla Costa, Emanuela
  • Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133 Milano, Italy. emanuela.dallacosta@unimi.it.
Tranquillo, Vito
  • Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna-Sezione diagnostica di Bergamo, 24125 Bergamo, Italy. vito.tranquillo@izsler.it.
Dai, Francesca
  • Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133 Milano, Italy. francesca.dai@unimi.it.
Minero, Michela
  • Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133 Milano, Italy. michela.minero@unimi.it.
Battini, Monica
  • Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133 Milano, Italy. monica.battini@unimi.it.
Mattiello, Silvana
  • Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133 Milano, Italy. silvana.mattiello@unimi.it.
Barbieri, Sara
  • Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 20133 Milano, Italy. sara.barbieri@unimi.it.
Ferrante, Valentina
  • Dipartimento di Scienze e Politiche Ambientali, Università degli Studi di Milano, 20133 Milano, Italy. valentina.ferrante@unimi.it.
Ferrari, Lorenzo
  • Dipartimento di Scienze e Politiche Ambientali, Università degli Studi di Milano, 20133 Milano, Italy. lorenzo.ferrari@unimi.it.
Zanella, Adroaldo
  • Department of Preventive Veterinary Medicine and Animal Health (VPS), University of São Paulo, São Paulo, SP 05508-270, Brazil. adroaldo.zanella@usp.br.
Canali, Elisabetta
  • Dipartimento di Scienze Agrarie e Ambientali - Produzione, Università degli Studi di Milano, Territorio, Agroenergia, 20133 Milano, Italy. elisabetta.canali@unimi.it.

Grant Funding

  • 266213 / Seventh Framework Programme

Conflict of Interest Statement

The authors declare no conflict of interest.

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Citations

This article has been cited 5 times.
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